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https://github.com/explosion/spaCy.git
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* Refactored transition system code now compiling. Still need to hook up label oracle, and test
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@ -112,18 +112,17 @@ cdef int count_right_kids(const TokenC* head) nogil:
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return _popcount(head.r_kids)
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cdef State* init_state(Pool mem, TokenC* sent, const int sent_length) except NULL:
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cdef int padded_len = sent_length + PADDING + PADDING
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cdef State* init_state(Pool mem, const TokenC* sent, const int sent_len) except NULL:
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cdef int padded_len = sent_len + PADDING + PADDING
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cdef State* s = <State*>mem.alloc(1, sizeof(State))
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s.stack = <int*>mem.alloc(padded_len, sizeof(int))
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for i in range(PADDING):
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s.stack[i] = -1
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s.stack += (PADDING - 1)
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assert s.stack[0] == -1
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s.sent = sent
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s.sent = <TokenC*>mem.alloc(sent_len, sizeof(TokenC))
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s.stack_len = 0
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s.i = 0
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s.sent_len = sent_length
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s.sent_len = sent_len
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push_stack(s)
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return s
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@ -33,14 +33,28 @@ cdef get_cost_func_t[N_MOVES] get_cost_funcs
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cdef class ArcEager(TransitionSystem):
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@classmethod
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def get_labels(cls, gold_parses):
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labels = {RIGHT: {}, LEFT: {}}
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for parse in gold_parses:
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for i, (head, label) in enumerate(zip(parse.heads, parse.labels)):
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if head > i:
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labels[RIGHT][label] = True
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else:
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labels[LEFT][label] = True
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return labels
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cdef Transition init_transition(self, int clas, int move, int label) except *:
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return Transition(
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score=0,
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clas=i,
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move=move,
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label=label,
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do=do_funcs[move],
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get_cost=get_cost_funcs[move])
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# TODO: Apparent Cython bug here when we try to use the Transition()
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# constructor with the function pointers
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cdef Transition t
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t.score = 0
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t.clas = clas
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t.move = move
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t.label = label
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t.do = do_funcs[move]
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t.get_cost = get_cost_funcs[move]
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return t
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cdef Transition best_valid(self, const weight_t* scores, const State* s) except *:
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cdef bint[N_MOVES] is_valid
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@ -111,8 +125,8 @@ do_funcs[BREAK] = _do_break
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cdef int _shift_cost(const Transition* self, const State* s, GoldParse gold) except -1:
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assert not at_eol(s)
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cost = 0
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cost += head_in_stack(s, s.i, gold.heads)
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cost += children_in_stack(s, s.i, gold.heads)
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cost += head_in_stack(s, s.i, gold.c_heads)
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cost += children_in_stack(s, s.i, gold.c_heads)
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if NON_MONOTONIC:
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cost += gold[s.stack[0]] == s.i
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# If we can break, and there's no cost to doing so, we should
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@ -126,9 +140,9 @@ cdef int _right_cost(const Transition* self, const State* s, GoldParse gold) exc
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cost = 0
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if gold[s.i] == s.stack[0]:
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return cost
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cost += head_in_buffer(s, s.i, gold.heads)
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cost += children_in_stack(s, s.i, gold.heads)
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cost += head_in_stack(s, s.i, gold.heads)
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cost += head_in_buffer(s, s.i, gold.c_heads)
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cost += children_in_stack(s, s.i, gold.c_heads)
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cost += head_in_stack(s, s.i, gold.c_heads)
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if NON_MONOTONIC:
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cost += gold[s.stack[0]] == s.i
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return cost
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@ -140,8 +154,8 @@ cdef int _left_cost(const Transition* self, const State* s, GoldParse gold) exce
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if gold[s.stack[0]] == s.i:
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return cost
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cost += head_in_buffer(s, s.stack[0], gold.heads)
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cost += children_in_buffer(s, s.stack[0], gold.heads)
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cost += head_in_buffer(s, s.stack[0], gold.c_heads)
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cost += children_in_buffer(s, s.stack[0], gold.c_heads)
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if NON_MONOTONIC and s.stack_len >= 2:
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cost += gold[s.stack[0]] == s.stack[-1]
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cost += gold[s.stack[0]] == s.stack[0]
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@ -150,9 +164,9 @@ cdef int _left_cost(const Transition* self, const State* s, GoldParse gold) exce
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cdef int _reduce_cost(const Transition* self, const State* s, GoldParse gold) except -1:
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cdef int cost = 0
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cost += children_in_buffer(s, s.stack[0], gold.heads)
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cost += children_in_buffer(s, s.stack[0], gold.c_heads)
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if NON_MONOTONIC:
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cost += head_in_buffer(s, s.stack[0], gold.heads)
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cost += head_in_buffer(s, s.stack[0], gold.c_heads)
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return cost
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@ -161,8 +175,8 @@ cdef int _break_cost(const Transition* self, const State* s, GoldParse gold) exc
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cdef int cost = 0
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# Number of deps between S0...Sn and N0...Nn
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for i in range(s.i, s.sent_len):
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cost += children_in_stack(s, i, gold.heads)
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cost += head_in_stack(s, i, gold.heads)
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cost += children_in_stack(s, i, gold.c_heads)
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cost += head_in_stack(s, i, gold.c_heads)
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return cost
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@ -1,7 +1,22 @@
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from cymem.cymem cimport Pool
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from ..structs cimport TokenC
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cdef class GoldParse:
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cdef int* heads
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cdef int* labels
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cdef Pool mem
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cdef int* c_heads
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cdef int* c_labels
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cdef int length
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cdef int loss
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cdef unicode raw_text
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cdef list words
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cdef list ids
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cdef list tags
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cdef list heads
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cdef list labels
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cdef int heads_correct(self, TokenC* tokens, bint score_punct=?) except -1
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@ -1,11 +1,20 @@
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cdef class GoldParse:
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def __init__(self):
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pass
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def __init__(self, raw_text, words, ids, tags, heads, labels):
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self.mem = Pool()
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self.loss = 0
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self.length = len(words)
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self.raw_text = raw_text
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self.words = words
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self.ids = ids
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self.tags = tags
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self.heads = heads
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self.labels = labels
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self.c_heads = <int*>self.mem.alloc(self.length, sizeof(int))
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self.c_labels = <int*>self.mem.alloc(self.length, sizeof(int))
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cdef int heads_correct(self, TokenC* tokens, bint score_punct=False) except -1:
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pass
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"""
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@classmethod
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def from_conll(cls, unicode sent_str):
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ids = []
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@ -50,42 +59,44 @@ cdef class GoldParse:
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for sent_str in tok_text.split('<SENT>')]
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return cls(raw_text, tokenized, ids, words, tags, heads, labels)
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cdef int heads_correct(self, TokenC* tokens, bint score_punct=False) except -1:
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pass
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def align_to_non_gold_tokens(self, tokens):
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# TODO
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tags = []
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heads = []
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labels = []
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orig_words = list(words)
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def align_to_tokens(self, tokens, label_ids):
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orig_words = list(self.words)
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annot = zip(self.ids, self.tags, self.heads, self.labels)
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self.ids = []
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self.tags = []
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self.heads = []
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self.labels = []
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missed = []
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for token in tokens:
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while annot and token.idx > annot[0][0]:
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miss_id, miss_tag, miss_head, miss_label = annot.pop(0)
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miss_w = words.pop(0)
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miss_w = self.words.pop(0)
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if not is_punct_label(miss_label):
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missed.append(miss_w)
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loss += 1
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self.loss += 1
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if not annot:
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tags.append(None)
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heads.append(None)
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labels.append(None)
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self.tags.append(None)
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self.heads.append(None)
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self.labels.append(None)
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continue
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id_, tag, head, label = annot[0]
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if token.idx == id_:
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tags.append(tag)
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heads.append(head)
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labels.append(label)
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self.tags.append(tag)
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self.heads.append(head)
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self.labels.append(label)
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annot.pop(0)
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words.pop(0)
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self.words.pop(0)
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elif token.idx < id_:
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tags.append(None)
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heads.append(None)
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labels.append(None)
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self.tags.append(None)
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self.heads.append(None)
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self.labels.append(None)
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else:
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raise StandardError
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return loss, tags, heads, labels
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mapped_heads = _map_indices_to_tokens(self.ids, self.heads)
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for i in range(self.length):
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self.c_heads[i] = mapped_heads[i]
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self.c_labels[i] = label_ids[self.labels[i]]
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return self.loss
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def is_punct_label(label):
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@ -116,6 +127,7 @@ def _parse_line(line):
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return id_, word, pos, head_idx, label
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"""
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# TODO
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def evaluate(Language, dev_loc, model_dir, gold_preproc=False):
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global loss
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@ -26,9 +26,10 @@ from thinc.learner cimport LinearModel
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from ..tokens cimport Tokens, TokenC
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from .arc_eager cimport TransitionSystem, Transition
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from .arc_eager import OracleError
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from .transition_system import OracleError
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from ._state cimport init_state, State, is_final, get_idx, get_s0, get_s1, get_n0, get_n1
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from .conll cimport GoldParse
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from . import _parse_features
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from ._parse_features cimport fill_context, CONTEXT_SIZE
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@ -60,10 +61,10 @@ def get_templates(name):
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cdef class GreedyParser:
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def __init__(self, model_dir):
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def __init__(self, model_dir, transition_system):
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assert os.path.exists(model_dir) and os.path.isdir(model_dir)
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self.cfg = Config.read(model_dir, 'config')
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self.moves = TransitionSystem(self.cfg.left_labels, self.cfg.right_labels)
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self.moves = transition_system(self.cfg.labels)
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templates = get_templates(self.cfg.features)
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self.model = Model(self.moves.n_moves, templates, model_dir)
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@ -74,23 +75,24 @@ cdef class GreedyParser:
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cdef atom_t[CONTEXT_SIZE] context
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cdef int n_feats
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cdef Pool mem = Pool()
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cdef State* state = init_state(mem, tokens.data, tokens.length) # TODO
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cdef State* state = init_state(mem, tokens.data, tokens.length)
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cdef Transition guess
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while not is_final(state):
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fill_context(context, state)
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scores = self.model.score(context)
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guess = self.moves.best_valid(scores, state)
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guess.do(&guess, state)
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tokens.set_parse(state.sent, self.moves.label_ids) # TODO
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tokens.set_parse(state.sent, self.moves.label_ids)
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return 0
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def train_sent(self, Tokens tokens, GoldParse gold, force_gold=False):
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def train(self, Tokens tokens, GoldParse gold, force_gold=False):
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cdef:
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int n_feats
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int cost
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const Feature* feats
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const weight_t* scores
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Transition guess
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Transition gold
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Transition best
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atom_t[CONTEXT_SIZE] context
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fill_context(context, state)
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scores = self.model.score(context)
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guess = self.moves.best_valid(scores, state)
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gold = self.moves.best_gold(scores, state, gold)
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best = self.moves.best_gold(scores, state, gold)
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cost = guess.get_cost(&guess, state, gold)
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self.model.update(context, guess.clas, best.clas, cost)
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if force_gold:
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@ -30,7 +30,7 @@ cdef class TransitionSystem:
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cdef Transition init_transition(self, int clas, int move, int label) except *
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cdef const Transition best_valid(self, const weight_t*, const State*) except *
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cdef Transition best_valid(self, const weight_t* scores, const State* state) except *
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cdef const Transition best_gold(self, const weight_t*, const State*,
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GoldParse gold) except *
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cdef Transition best_gold(self, const weight_t* scores, const State* state,
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GoldParse gold) except *
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@ -7,6 +7,10 @@ from thinc.typedefs cimport weight_t
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cdef weight_t MIN_SCORE = -90000
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class OracleError(Exception):
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pass
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cdef class TransitionSystem:
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def __init__(self, dict labels_by_action):
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self.mem = Pool()
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raise NotImplementedError
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cdef Transition best_gold(self, const weight_t* scores, const State* s,
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const TokenC* gold) except *:
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GoldParse gold) except *:
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cdef Transition best
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cdef weight_t score = MIN_SCORE
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cdef int i
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